From 34bd30415dd93a2425ce566627e24ee9483ada3e Mon Sep 17 00:00:00 2001 From: Mario Mulansky Date: Thu, 20 Sep 2018 10:49:42 -0700 Subject: Spike Order support (#39) * reorganized directionality module * further refactoring of directionality * completed python directionality backend * added SPIKE-Sync based filtering new function filter_by_spike_sync removes spikes that have a multi-variate Spike Sync value below some threshold not yet fully tested, python backend missing. * spike sync filtering, cython sim ann Added function for filtering out events based on a threshold for the spike sync values. Usefull for focusing on synchronous events during directionality analysis. Also added cython version of simulated annealing for performance. * added coincidence single profile to python backend missing function in python backend added, identified and fixed a bug in the implementation as well * updated test case to new spike sync behavior * python3 fixes * another python3 fix * reorganized directionality module * further refactoring of directionality * completed python directionality backend * added SPIKE-Sync based filtering new function filter_by_spike_sync removes spikes that have a multi-variate Spike Sync value below some threshold not yet fully tested, python backend missing. * spike sync filtering, cython sim ann Added function for filtering out events based on a threshold for the spike sync values. Usefull for focusing on synchronous events during directionality analysis. Also added cython version of simulated annealing for performance. * added coincidence single profile to python backend missing function in python backend added, identified and fixed a bug in the implementation as well * updated test case to new spike sync behavior * python3 fixes * another python3 fix * Fix absolute imports in directionality measures * remove commented code * Add directionality to docs, bump version * Clean up directionality module, add doxy. * Remove debug print from tests * Fix bug in calling Python backend * Fix incorrect integrals in PieceWiseConstFunc (#36) * Add (some currently failing) tests for PieceWiseConstFunc.integral * Fix implementation of PieceWiseConstFunc.integral Just by adding a special condition for when we are only taking an integral "between" two edges of a PieceWiseConstFunc All tests now pass. Fixes #33. * Add PieceWiseConstFunc.integral tests for ValueError * Add testing bounds of integral * Raise ValueError in function implementation * Fix incorrect integrals in PieceWiseLinFunc (#38) Integrals of piece-wise linear functions were incorrect if the requested interval lies completely between two support points. This has been fixed, and a unit test exercising this behavior was added. Fixes #38 * Add Spike Order example and Tutorial section Adds an example computing spike order profile and the optimal spike train order. Also adds a section on spike train order to the tutorial. --- test/test_sync_filter.py | 95 ++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 95 insertions(+) create mode 100644 test/test_sync_filter.py (limited to 'test/test_sync_filter.py') diff --git a/test/test_sync_filter.py b/test/test_sync_filter.py new file mode 100644 index 0000000..e259903 --- /dev/null +++ b/test/test_sync_filter.py @@ -0,0 +1,95 @@ +""" test_sync_filter.py + +Tests the spike sync based filtering + +Copyright 2015, Mario Mulansky + +Distributed under the BSD License + +""" + +from __future__ import print_function +import numpy as np +from numpy.testing import assert_equal, assert_almost_equal, \ + assert_array_almost_equal + +import pyspike as spk +from pyspike import SpikeTrain + + +def test_single_prof(): + st1 = np.array([1.0, 2.0, 3.0, 4.0]) + st2 = np.array([1.1, 2.1, 3.8]) + st3 = np.array([0.9, 3.1, 4.1]) + + # cython implementation + try: + from pyspike.cython.cython_profiles import \ + coincidence_single_profile_cython as coincidence_impl + except ImportError: + from pyspike.cython.python_backend import \ + coincidence_single_python as coincidence_impl + + sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0), + SpikeTrain(st2, 5.0)) + + coincidences = np.array(coincidence_impl(st1, st2, 0, 5.0, 0.0)) + print(coincidences) + for i, t in enumerate(st1): + assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t], + "At index %d" % i) + + coincidences = np.array(coincidence_impl(st2, st1, 0, 5.0, 0.0)) + for i, t in enumerate(st2): + assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t], + "At index %d" % i) + + sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0), + SpikeTrain(st3, 5.0)) + + coincidences = np.array(coincidence_impl(st1, st3, 0, 5.0, 0.0)) + for i, t in enumerate(st1): + assert_equal(coincidences[i], sync_prof.y[sync_prof.x == t], + "At index %d" % i) + + st1 = np.array([1.0, 2.0, 3.0, 4.0]) + st2 = np.array([1.0, 2.0, 4.0]) + + sync_prof = spk.spike_sync_profile(SpikeTrain(st1, 5.0), + SpikeTrain(st2, 5.0)) + + coincidences = np.array(coincidence_impl(st1, st2, 0, 5.0, 0.0)) + for i, t in enumerate(st1): + expected = sync_prof.y[sync_prof.x == t]/sync_prof.mp[sync_prof.x == t] + assert_equal(coincidences[i], expected, + "At index %d" % i) + + +def test_filter(): + st1 = SpikeTrain(np.array([1.0, 2.0, 3.0, 4.0]), 5.0) + st2 = SpikeTrain(np.array([1.1, 2.1, 3.8]), 5.0) + st3 = SpikeTrain(np.array([0.9, 3.1, 4.1]), 5.0) + + # filtered_spike_trains = spk.filter_by_spike_sync([st1, st2], 0.5) + + # assert_equal(filtered_spike_trains[0].spikes, [1.0, 2.0, 4.0]) + # assert_equal(filtered_spike_trains[1].spikes, [1.1, 2.1, 3.8]) + + # filtered_spike_trains = spk.filter_by_spike_sync([st2, st1], 0.5) + + # assert_equal(filtered_spike_trains[0].spikes, [1.1, 2.1, 3.8]) + # assert_equal(filtered_spike_trains[1].spikes, [1.0, 2.0, 4.0]) + + filtered_spike_trains = spk.filter_by_spike_sync([st1, st2, st3], 0.75) + + for st in filtered_spike_trains: + print(st.spikes) + + assert_equal(filtered_spike_trains[0].spikes, [1.0, 4.0]) + assert_equal(filtered_spike_trains[1].spikes, [1.1, 3.8]) + assert_equal(filtered_spike_trains[2].spikes, [0.9, 4.1]) + + +if __name__ == "main": + test_single_prof() + test_filter() -- cgit v1.2.3